arXiv cs.LG
· Papers
Dynamics Models for Offline Hyperparameter Selection in Real-World RL
arXiv:2608.11349v1 Announce Type: new Abstract: A key obstacle to deploying reinforcement learning in real-world systems is hyperparameter selection, particularly when simulators are unavailable and online experimentation is costly. Prior work has proposed calibration models trained on offline data to approximate envir